| 基于PCA-概率神经网络的P2P流量分类方法研究 |
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| 引用本文： | 贺静,赵峦.基于PCA-概率神经网络的P2P流量分类方法研究[J].电脑开发与应用,2011,24(7):18-20. |
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| 作者姓名： | 贺静 赵峦 |
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| 作者单位： | 1. 太原理工大学信息化管理与建设中心 太原030024
2. 解放军66410部队通信管理中心 北京 100042 |
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| 摘 要： | 随着P2P快速增长带来的网络拥塞等诸多问题,准确识别P2P流量对流量控制具有重要的实际意义.提出利用PCA特征选择方法选择最优特征子集,使用概率神经网络方法对P2P流量与常规流量进行分类.实验结果表明,该方法的分类精确度与准确度有了明显的提高.
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| 关 键 词： | 对等网 主成分分析 概率神经网络 流量分类 |
Research on P2P Traffic Classification Based on PCA-Probabilistic Neural Network |
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| He Jing et al.Research on P2P Traffic Classification Based on PCA-Probabilistic Neural Network[J].Computer Development & Applications,2011,24(7):18-20. |
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| Authors: | He Jing |
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| Affiliation: | He Jing et al |
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| Abstract: | As the rapid increase of P2P application,many network problems occur,identify P2P traffic accurately has an important practical significance to further flow control.The paper utilize a PCA feature selection method,which can choose the best feature subsets.It uses probabilistic neural network algorithm to classify the network traffic.The experiment indicates that this method is better exactitude and accuracy. |
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| Keywords: | P2P PCA PNN traffic classificati |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
